DocumentCode :
3767216
Title :
A comparative study of various community detection algorithms in the mobile social network
Author :
Ankit Didwania;Zunnun Narmawala
Author_Institution :
IT Department, Faculty of Technology, Dharmsinh Desai University, Nadiad, Gujarat, India
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
Mobile social network is a type of delay tolerant network of mobile devices in which there is no end-to-end path available in advance for communication. It works on the principle of a store-carry-forward mechanism. The community is a very useful property of the mobile social network as humans are social animals and they like to live in a community. Such community structure enables efficient communication between devices carried by humans without any infrastructure. We have analyzed various community detection methods and identified those suitable for mobile social network. We have also analyzed various existing distributed community detection algorithms in mobile social networks based on important parameters like complexity and type of community detected. Such analysis will help in discovering strengths and shortcomings of various existing algorithms. As the mobile social network is self-organizing real network working on highly resource constraint mobile devices, it is necessary to enable each mobile device to detect its own community with minimal information, computation and space requirements. This is a very challenging task and very little work is done in it. So there is an immense opportunity available for research in this area.
Keywords :
"Social network services","Mobile computing","Mobile communication","Mobile handsets","Detection algorithms","Clustering algorithms","Delays"
Publisher :
ieee
Conference_Titel :
Engineering (NUiCONE), 2015 5th Nirma University International Conference on
Type :
conf
DOI :
10.1109/NUICONE.2015.7449651
Filename :
7449651
Link To Document :
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